Managing life cycle for data processing applications—especially enterprise data processing applications—is important: data processing application often consumes significant computing resources, e.g., when loading, transmitting, or visualizing large data sets.
Difficulties abound, however. One technical problem is that an application's performance is often times limited by the speed of the several networks (e.g., a cellular network, a cable network, and a WIFI network) over which data are transmitted. For example, loading 100 MB data from a remote enterprise data server to a user's IPAD device via a 10 Mbps cable network and an in-home WIFI network may take several minutes, causing an appreciable amount of user frustration.
Another technical problem is that, data transmissions often takes a significant toll on a device's power usage. This problem is exacerbated when involved are tablet computers (e.g., an APPLE IPAD device) and smartphones (e.g., an APPLE IPHONE device), both of which rely heavily on battery powers.
A third technical problem is that, frequent data transmissions consume significant computing power, causing other applications (sometime even a device itself) to “freeze.”
There therefore is a need for improved techniques for detecting potential data quality problems.